April 24, 2024

Refocusing Dark Matter Search: New Supercomputer Simulations Refine Axion Mass

In a simulation of the early universe, quickly after the Big Bang, tornado-like strings (dark blue loop) shake off axion particles. These axions must still be around today, and could be the dark matter that astrophysicists have actually been looking for. Credit: Malte Buschmann, Princeton University
Using adaptive mesh refinement, supercomputer simulation narrows axion mass range.
Physicists browsing– unsuccessfully– for todays most preferred candidate for dark matter, the axion, have been searching in the incorrect location, according to a brand-new supercomputer simulation of how axions were produced shortly after the Big Bang 13.6 billion years back.
Utilizing brand-new calculational strategies and among the worlds biggest computers, Benjamin Safdi, assistant professor of physics at the University of California, Berkeley; Malte Buschmann, a postdoctoral research partner at Princeton University; and colleagues at MIT and Lawrence Berkeley National Laboratory simulated the era when axions would have been produced, approximately a billionth of a billionth of a billionth of a second after the universe came into existence and after the epoch of cosmic inflation.

The simulation at Berkeley Labs National Research Scientific Computing Center (NERSC) found the axions mass to be more than two times as huge as theorists and experimenters have actually believed: in between 40 and 180 microelectron volts (micro-eV, or µeV), or about one 10-billionth the mass of the electron. The goal of this simulation is to exactly measure how much axion radiation is produced by the diminishing string network, and from that compute the expected mass of the axion particle. In the 1980s, the axion began to be seen likewise as a candidate for dark matter, and the very first attempts to detect axions were released.” You can believe of these strings as composed of axions hugging the vortices while these strings whip around forming loops, connecting, going through a lot of violent dynamical procedures throughout the expansion of our universe, and the axions hugging the sides of these strings are trying to hold on for the trip,” Safdi said.” Over the years, brand-new theoretical understanding has loosened up the restrictions on the axion mass; it can be anywhere within 15 orders of magnitude, if you think about the possibility that axions formed before inflation.

The simulation at Berkeley Labs National Research Scientific Computing Center (NERSC) found the axions mass to be more than two times as huge as theorists and experimenters have thought: in between 40 and 180 microelectron volts (micro-eV, or µeV), or about one 10-billionth the mass of the electron. There are signs, Safdi stated, that the mass is close to 65 µeV. Because physicists started looking for the axion 40 years back, quotes of the mass have actually varied commonly, from a couple of µeV to 500 µeV.
” We supply over a thousandfold enhancement in the dynamic range of our axion simulations relative to prior work and clear up a 40-year old concern regarding the axion mass and axion cosmology,” Safdi said.
Zooming in on a little part of the supercomputer simulation of the early universe shows the development of topological flaws called strings (yellow), which vibrate and writhe at speeds approaching the speed of light. As the strings twist, vibrate and diminish, they emit radiation in the form of axions (blue). This axion radiation might then become the dark matter in our universe. The goal of this simulation is to precisely measure just how much axion radiation is produced by the diminishing string network, and from that calculate the anticipated mass of the axion particle. Credit: Malte Buschmann, Princeton University
The more definitive mass means that the most typical type of experiment to spot these evasive particles– a microwave resonance chamber including a strong electromagnetic field, in which scientists hope to snag the conversion of an axion into a faint electro-magnetic wave– will not have the ability to identify them, no matter how much the experiment is tweaked. The chamber would have to be smaller sized than a couple of centimeters on a side to spot the higher-frequency wave from a higher-mass axion, Safdi said, and that volume would be too small to capture enough axions for the signal to increase above the noise.
” Our work offers the most accurate quote to date of the axion mass and indicate a specific series of masses that is not presently being checked out in the laboratory,” he stated. “I actually do believe it makes sense to focus experimental efforts on 40 to 180 µeV axion masses, however theres a great deal of work tailoring up to go after that mass variety.”
One newer type of experiment, a plasma haloscope, which searches for axion excitations in a metamaterial– a solid-state plasma– need to be sensitive to an axion particle of this mass, and could possibly detect one.
” The standard studies of these three-dimensional varieties of great wires have worked out surprisingly well, far better than we ever expected,” stated Karl van Bibber, a UC Berkeley teacher of nuclear engineering who is developing a prototype of the plasma haloscope while also taking part in a microwave cavity axion search called the HAYSTAC experiment. “Bens most current outcome is really amazing. If the post-inflation situation is right, after 4 years, discovery of the axion might be significantly accelerated.”
, if axions actually exist.
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The work will be published today (February 25, 2022) in the journal Nature Communications.
Axion leading candidate for dark matter
Dark matter is a mystical substance that astronomers understand exists– it affects the motions of every star and galaxy– however which communicates so weakly with the things of stars and galaxies that it has actually avoided detection. That doesnt suggest dark matter cant be studied and even weighed. Astronomers know quite specifically just how much dark matter exists in the Milky Way Galaxy and even in the whole universe: 85% of all matter in the universes.
To date, dark matter searches have focused on huge compact things in the halo of our galaxy (called enormous compact halo objects, or MACHOs), weakly interacting massive particles (WIMPs) and even unseen black holes. None showed up a likely candidate.
” Dark matter is most of the matter in the universe, and we have no idea what it is. “We think it is a new particle we do not understand about, and the axion could be that particle.
Not strictly a WIMP, the axion likewise engages weakly with regular matter. The axion, according to theory, reduces this precession in the neutron.
” Still to this day, the axion is the finest idea we have about how to describe these weird observations about the neutron,” Safdi said.
In the 1980s, the axion started to be seen likewise as a candidate for dark matter, and the first efforts to detect axions were introduced. Utilizing the equations of the well-vetted theory of basic particle interactions, the so-called Standard Model, in addition to the theory of the Big Bang, the Standard Cosmological Model, it is possible to determine the axions accurate mass, but the equations are so tough that to date we have just estimates, which have varied profoundly. Given that the mass is understood so imprecisely, searches using microwave cavities– essentially elaborate radio receivers– need to tune through countless frequency channels to look for the one representing the axion mass.
” With these axion experiments, they do not understand what station theyre supposed to be tuning to, so they need to scan over several possibilities,” Safdi stated.
Safdi and his team produced the most recent, though inaccurate, axion mass quote that experimentalists are currently targeting. As they worked on improved simulations, they approached a team from Berkeley Lab that had developed a specialized code for a much better simulation method called adaptive mesh refinement.
The technique permitted Safdis simulation to see thousands of times more information around the areas where axions are generated, permitting a more exact determination of the total variety of axions produced and, provided the total mass of dark matter in deep space, the axion mass. The simulation employed 69,632 physical computer system processing unit (CPU) cores of the Cori supercomputer with nearly 100 terabytes of random gain access to memory (RAM), making the simulation one of the largest dark matter simulations of any kind to date.
The simulation showed that after the inflationary date, little twisters, or vortices, form like ropey strings in the early universe and toss off axions like riders bucked from a bronco.
” You can consider these strings as made up of axions hugging the vortices while these strings whip around forming loops, connecting, undergoing a lot of violent dynamical processes throughout the expansion of our universe, and the axions hugging the sides of these strings are attempting to hang on for the trip,” Safdi stated. “But when something too violent occurs, they simply get tossed off and whip away from these strings. And those axions which get shaken off of the strings wind up ending up being the dark matter much later on.”
By monitoring the axions that are whipped off, scientists have the ability to forecast the quantity of dark matter that was produced.
Adaptive mesh refinement permitted the scientists to replicate the universe a lot longer than previous simulations and over a much larger spot of the universe than previous simulations.
” We fix for the axion mass both in a more clever way and also by throwing simply as much computing power as we could possibly find onto this issue,” Safdi stated. We simply require to replicate a huge sufficient patch of the universe for a long adequate duration of time, such that we capture all of the dynamics that we understand are consisted of within that box.”
The group is dealing with a brand-new supercomputing cluster now being developed at Berkeley Lab that will make it possible for simulations that will provide a much more exact mass. Called Perlmutter, after Saul Perlmutter, a UC Berkeley and Berkeley Lab physicist who won the 2011 Nobel Prize in Physics for discovering the accelerating expansion of deep space driven by so-called dark energy, the next-generation supercomputer will quadruple the computing power of NERSC.
” We wish to make even bigger simulations at even higher resolution, which will allow us to shrink these mistake bars, hopefully down to the 10% level, so we can tell you a really accurate number, like 65 plus or minus 2 micro-eV. That then truly changes the video game experimentally, since then it would become a much easier experiment to verify or leave out the axion in such a narrow mass variety,” Safdi stated.
For van Bibber, who was not a member of Safdis simulation team, the brand-new mass price quote checks the limits of microwave cavities, which work less well at high frequencies. While the lower limit of the mass variety is still within the ability of the HAYSTAC experiment to identify, he is enthused about the plasma haloscope.
” Over the years, brand-new theoretical understanding has actually loosened the restrictions on the axion mass; it can be anywhere within 15 orders of magnitude, if you think about the possibility that axions formed before inflation. An actual resonator for a real experiment is still some ways away, but this might be the way to go to get to Safdis anticipated mass.”
When simulations provide an even more precise mass, the axion may, in truth, be simple to find.
” It was really important that we coordinated with this computer science group at Berkeley Lab,” Safdi said. “We actually broadened beyond the physics field and actually made this a computing science issue.”
Reference: “Dark matter from axion strings with adaptive mesh refinement” 25 February 2022, Nature Communications.DOI: 10.1038/ s41467-022-28669-y.
Safdis colleagues consist of Malte Buschmann of Princeton; MIT postdoctoral fellow Joshua Foster; Anson Hook of the University of Maryland; and Adam Peterson, Don Willcox and Weiqun Zhang of Berkeley Labs Center for Computational Sciences and Engineering. The research was mostly funded by the U.S. Department of Energy through the Exascale Computing Project (17-SC-20-SC) and through the Early Career program (DESC0019225).